Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
It's been a while. What can I do to draw some attention to this request? Is
this issue not relevant enough? Thanks for reconsideration @felixcheung @brkyvz
@zsxwing
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Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
@felixcheung will this be merged?
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Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
Sorry for being inactive. All good with this?
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Github user arzt commented on a diff in the pull request:
https://github.com/apache/spark/pull/17774#discussion_r113871876
--- Diff:
external/kafka-0-10/src/test/scala/org/apache/spark/streaming/kafka010/DirectKafkaStreamSuite.scala
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@@ -617,6 +617,94 @@ class
Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
I changed the max messages per partition to be at least 1. Agreed?
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Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
@koeninger I agree that assuming a long batch size is wrong, not sure
whether it even matters.
But what if for one partition there is no lack in the current batch? Then
fetching 1 message
Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
To run tests or debug using IntelliJ:
`mvn test -DforkMode=never -pl external/kafka-0-8
"-Dsuites=org.apache.spark.streaming.kafka.DirectKafkaStreamSuite
maxMessagesPerPartition"`
-
Github user arzt commented on the issue:
https://github.com/apache/spark/pull/17774
Thanks for your valuable feedback. I added tests as suggested by
@JasonMWhite . @koeninger the estimated rate is per second summed over all
partitions, is it? The batch time usually is longer. So even
GitHub user arzt opened a pull request:
https://github.com/apache/spark/pull/17774
[SPARK-18371][Streaming] Spark Streaming backpressure generates batch with
large number of records
## What changes were proposed in this pull request?
Omit rounding of backpressure rate
